A road condition planning method and device
A road condition and road technology, applied in the traffic control system, instrument, traffic control system of road vehicles, etc., can solve the problems of limited congestion status and inaccurate prediction of congested road sections, and achieves reduction of travel time, wide coverage, and convenience. Select the effect of the road
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Embodiment 1
[0047] refer to figure 1 , which shows the flow chart of the road condition planning method provided by Embodiment 1 of the present invention.
[0048] Step 101, predict the distribution of travel information of each vehicle in a preset future time period according to a preset travel prediction model.
[0049] In the embodiment of the present invention, a travel prediction model is preset, and the travel prediction model is used to predict the travel status of the vehicle, that is, the travel information distribution of each vehicle in the future period can be predicted through the travel prediction model.
[0050] Wherein, the future time period is a preset time period to be predicted. For example, if the current time is 12 o'clock, the future time period can be set as 16 o'clock to 20 o'clock of the current day. The driving information distribution includes relevant information of each vehicle traveling in the road network, such as whether each vehicle travels in the future...
Embodiment 2
[0069] refer to figure 2 , which shows the flow chart of the road condition planning method provided by Embodiment 2 of the present invention.
[0070] Step 201, input the preset future period into the preset travel prediction model to obtain the state probability corresponding to each vehicle.
[0071] In the embodiment of the present invention, each travel prediction model must first be established, and the travel prediction model includes: a travel purpose prediction model, a travel route prediction model, a driving behavior prediction model, and an external influence model. Wherein, step 201 mainly performs prediction according to the first three models.
[0072] When establishing a travel prediction model, the vehicle information of each vehicle history is firstly collected, and a model is built based on the vehicle information of each vehicle history to obtain a travel prediction model.
[0073] Wherein, the vehicle information is information related to the historical...
Embodiment 3
[0131] An embodiment is adopted below to specifically discuss the road condition planning method.
[0132] refer to image 3 , which shows the road schematic diagram provided by Embodiment 3 of the present invention.
[0133] In this embodiment, two prediction schemes are given, as follows:
[0134] 1. Predict the traffic situation of road A in T1 in the next 5 minutes.
[0135] 1. Assume that the total length of road A is 1000 meters, and it is divided into ten sections according to the granularity of 100 meters, which are marked as A1, A2, ..., A10. Take the road information of each section, (such as A2 section one-way two-lane, 3-meter road width, straight road section, 60km / h speed limit, 1 traffic light, etc.), and use this information as input to calculate each section of road A Vehicle traffic volume, such as A1=2500, A2=1850, A3=2000, etc.
[0136] 2. Use the travel purpose prediction model, travel route prediction model and driving behavior prediction model in the...
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